Analysis overview

This systematic review and meta-analysis evaluated the effects of antipsychotic treatment on locomotor activity measured during social interaction tests in animal models. Effect sizes were calculated as Hedges’ g and synthesized using multilevel random-effects models to account for dependency between multiple outcomes within experiments and studies.

Study landscape and evidence distribution

Alluvial plot

Distribution of evidence across species, NMDA antagonists, and antipsychotics. Alluvial plot illustrating how effect sizes are distributed across animal species, NMDA receptor antagonists used to induce social deficits, and antipsychotic drugs tested for reversal.

Evidence maps

Evidence maps of experimental design characteristics.
Bubble size represents the number of effect sizes (k), and color indicates the mean Hedges’ g within each cell.

Main meta-analysis

Overall effect

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.044  0.209     19     no         study_id 
## sigma^2.2  0.090  0.301     48     no  study_id/exp_id 
## 
## Test for Heterogeneity:
## Q(df = 121) = 678.702, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Model Results:
## 
## estimate     seÂą    tvalÂą     dfÂą   pvalÂą   ci.lbÂą   ci.ubÂą      
##   -0.493  0.096   -5.133   13.06   <.001   -0.701   -0.286   *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t-test and confidence interval, df: Satterthwaite approx)

Multilevel random-effects meta-analysis with robust variance estimation.

Orchard plot

Overall effect on locomotor activity (social interaction test). Orchard plot summarizing study-level pooled effects with multilevel heterogeneity.

Prediction interval for the overall effect

##     estimate      ci_lb      ci_ub     pi_lb    pi_ub
## 1 -0.4931826 -0.7006607 -0.2857045 -1.310629 0.324264

Prediction interval for the overall effect. The 95% prediction interval reflects expected variability in the true effect size of a future study beyond sampling error.

##            Component I.....
## 1           I2_Total   33.7
## 2        I2_study_id   11.0
## 3 I2_study_id/exp_id   22.7

Multilevel heterogeneity estimates (I²).

Publication bias

Funnel plots

Funnel plot using standard error.

Funnel plot using inverse square root of total sample size.

Precision Effect Test (PET)

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.531  0.729     19     no         study_id 
## sigma^2.2  0.040  0.201     48     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 120) = 329.578, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 6.05) = 51.459, p-val < .001
## 
## Model Results:
## 
##           estimate     seÂą    tvalÂą    dfÂą   pvalÂą    ci.lbÂą   ci.ubÂą      
## intrcpt      4.327  0.612    7.073   9.07   <.001     2.945    5.709   *** 
## sqrt(vi)    -9.256  1.290   -7.173   6.05   <.001   -12.407   -6.105   *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

PET (Precision Effect Test) model with robust variance estimation. The PET model evaluates small-study bias by regressing effect size on study precision.

Precision Effect Estimate with Standard Error (PEESE)

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.063  0.251     19     no         study_id 
## sigma^2.2  0.000  0.000     48     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 120) = 390.292, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 2.7) = 9.870, p-val = 0.059
## 
## Model Results:
## 
##          estimate     seÂą    tvalÂą    dfÂą   pvalÂą   ci.lbÂą  ci.ubÂą    
## intrcpt     0.563  0.333    1.691   8.71   0.126   -0.194   1.320     
## vi         -4.110  1.308   -3.142    2.7   0.059   -8.547   0.328   . 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

PEESE (Precision Effect Estimate with Standard Error) model with robust variance estimation. The PEESE model provides an alternative bias-adjusted estimate using study variance.

Time-lag bias

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.051  0.225     19     no         study_id 
## sigma^2.2  0.095  0.308     48     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 120) = 678.120, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 8.88) = 0.278, p-val = 0.611
## 
## Model Results:
## 
##          estimate     seÂą    tvalÂą    dfÂą   pvalÂą   ci.lbÂą   ci.ubÂą      
## intrcpt    -0.506  0.104   -4.882   8.86   <.001   -0.741   -0.271   *** 
## year_c      0.006  0.012    0.528   8.88   0.611   -0.021    0.034       
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

Time-lag meta-regression model. This model tests whether effect sizes change systematically over publication time. A significant slope would indicate temporal trends such as decline or inflation of reported effects.

Time-lag bias: effect size as a function of publication year.

Moderators

Moderator analyses were conducted using multilevel meta-analytic models with robust variance estimation to examine whether effect sizes differed across experimental and biological characteristics. Orchard plots display pooled effects for each moderator level, with study-level clustering and multilevel heterogeneity taken into account.

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.137  0.370     19     no         study_id 
## sigma^2.2  0.135  0.368     48     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 113) = 669.383, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Test of Moderators (coefficients 1:9):Âą
## F(df1 = 9, df2 = 0) = 0.000, p-val = NA
## 
## Model Results:
## 
##                         estimate     seÂą    tvalÂą    dfÂą   pvalÂą    ci.lbÂą 
## atp_drugAripiprazole      -0.827  0.706   -1.172   1.01   0.448    -9.593  
## atp_drugCariprazine       -1.244  0.170   -7.312   2.39   0.011    -1.872  
## atp_drugChlorpromazine     0.025  0.434    0.058   1.15   0.962    -4.072  
## atp_drugClozapine         -0.299  0.213   -1.403   8.94   0.194    -0.782  
## atp_drugHaloperidol       -0.712  0.194   -3.663   5.59   0.012    -1.195  
## atp_drugOlanzapine        -0.454  0.130   -3.504   1.74   0.088    -1.098  
## atp_drugQuetiapine        -0.791  0.347   -2.280   1.25   0.221    -3.560  
## atp_drugRisperidone       -0.492  0.221   -2.230   4.98   0.076    -1.059  
## atp_drugSulpiride         -0.592  2.239   -0.264      1   0.835   -29.047  
##                          ci.ubÂą    
## atp_drugAripiprazole     7.939     
## atp_drugCariprazine     -0.615   * 
## atp_drugChlorpromazine   4.122     
## atp_drugClozapine        0.184     
## atp_drugHaloperidol     -0.228   * 
## atp_drugOlanzapine       0.190   . 
## atp_drugQuetiapine       1.979     
## atp_drugRisperidone      0.076   . 
## atp_drugSulpiride       27.863     
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.061  0.247     19     no         study_id 
## sigma^2.2  0.090  0.300     48     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 120) = 678.174, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Test of Moderators (coefficients 1:2):Âą
## F(df1 = 2, df2 = 7.36) = 16.062, p-val = 0.002
## 
## Model Results:
## 
##                       estimate     seÂą    tvalÂą     dfÂą   pvalÂą   ci.lbÂą 
## atp_scheduleAcute       -0.438  0.143   -3.064   10.49   0.011   -0.755  
## atp_scheduleRepeated    -0.575  0.102   -5.608    4.31   0.004   -0.851  
##                        ci.ubÂą     
## atp_scheduleAcute     -0.122    * 
## atp_scheduleRepeated  -0.298   ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.019  0.139     19     no         study_id 
## sigma^2.2  0.064  0.253     48     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 118) = 665.855, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Test of Moderators (coefficients 1:4):Âą
## F(df1 = 4, df2 = 2.4) = 4.153, p-val = 0.171
## 
## Model Results:
## 
##                                          estimate     seÂą    tvalÂą    dfÂą 
## atp_administration_routeIntraperitoneal    -0.531  0.164   -3.241    5.7  
## atp_administration_routeOral               -0.287  0.281   -1.020   4.21  
## atp_administration_routeSubcutaneous       -0.473  0.118   -4.000   2.46  
## atp_administration_routeUnclear            -2.727  1.209   -2.257      1  
##                                           pvalÂą    ci.lbÂą   ci.ubÂą    
## atp_administration_routeIntraperitoneal  0.019    -0.938   -0.125   * 
## atp_administration_routeOral             0.363    -1.053    0.479     
## atp_administration_routeSubcutaneous     0.040    -0.901   -0.045   * 
## atp_administration_routeUnclear          0.266   -18.084   12.629     
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.054  0.232     19     no         study_id 
## sigma^2.2  0.085  0.291     48     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 119) = 672.955, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Test of Moderators (coefficients 1:3):Âą
## F(df1 = 3, df2 = 2.46) = 5.617, p-val = 0.122
## 
## Model Results:
## 
##                               estimate     seÂą    tvalÂą    dfÂą   pvalÂą   ci.lbÂą 
## nmda_antagonistKetamine         -0.402  0.242   -1.663      1   0.344   -3.459  
## nmda_antagonistMK-801           -0.253  0.151   -1.672   6.38   0.143   -0.618  
## nmda_antagonistPhencyclidine    -0.703  0.141   -4.998   5.25   0.004   -1.059  
##                                ci.ubÂą     
## nmda_antagonistKetamine        2.655      
## nmda_antagonistMK-801          0.112      
## nmda_antagonistPhencyclidine  -0.346   ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.048  0.218     19     no         study_id 
## sigma^2.2  0.095  0.308     48     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 120) = 677.599, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 12.43) = 16.039, p-val = 0.002
## 
## Model Results:
## 
##             estimate     seÂą                 tvalÂą     dfÂą   pvalÂą   ci.lbÂą 
## intrcpt       -0.111  0.000   -99554341690776.812   11.96   <.001   -0.111  
## speciesRat    -0.398  0.099                -4.005   12.43   0.002   -0.614  
##              ci.ubÂą      
## intrcpt     -0.111   *** 
## speciesRat  -0.182    ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.097  0.312     19     no         study_id 
## sigma^2.2  0.082  0.287     48     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 119) = 678.568, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Test of Moderators (coefficients 1:3):Âą
## F(df1 = 3, df2 = 3.63) = 5.125, p-val = 0.084
## 
## Model Results:
## 
##                                                   estimate     seÂą    tvalÂą 
## developmental_stage_inductionAdult                  -0.716  0.498   -1.439  
## developmental_stage_inductionJuvenile/Adolescent    -0.579  0.276   -2.095  
## developmental_stage_inductionUnclear                -0.436  0.105   -4.169  
##                                                     dfÂą   pvalÂą   ci.lbÂą 
## developmental_stage_inductionAdult                1.63   0.312   -3.394  
## developmental_stage_inductionJuvenile/Adolescent  2.95   0.129   -1.467  
## developmental_stage_inductionUnclear              8.79   0.003   -0.673  
##                                                    ci.ubÂą     
## developmental_stage_inductionAdult                 1.961      
## developmental_stage_inductionJuvenile/Adolescent   0.309      
## developmental_stage_inductionUnclear              -0.199   ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

## 
## Multivariate Meta-Analysis Model (k = 122; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.355  0.596     19     no         study_id 
## sigma^2.2  0.115  0.339     48     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 106) = 657.999, p-val < .001
## 
## Number of estimates:   122
## Number of clusters:    19
## Estimates per cluster: 1-20 (mean: 6.42, median: 6)
## 
## Model Results:
## 
##                                                     estimate     seÂą    tvalÂą 
## atp_nmda_interactionClozapine Ă— Ketamine              -0.674  0.642   -1.050  
## atp_nmda_interactionHaloperidol Ă— Ketamine             0.151  0.374    0.403  
## atp_nmda_interactionRisperidone Ă— Ketamine             0.013  0.405    0.032  
## atp_nmda_interactionAripiprazole Ă— MK-801             -0.351  0.473   -0.741  
## atp_nmda_interactionClozapine Ă— MK-801                 0.015  0.374    0.040  
## atp_nmda_interactionHaloperidol Ă— MK-801              -0.586  0.311   -1.881  
## atp_nmda_interactionRisperidone Ă— MK-801              -0.685  0.712   -0.962  
## atp_nmda_interactionAripiprazole Ă— Phencyclidine      -2.021  0.000       NA  
## atp_nmda_interactionCariprazine Ă— Phencyclidine       -1.434  0.323   -4.437  
## atp_nmda_interactionChlorpromazine Ă— Phencyclidine     0.045  0.298    0.149  
## atp_nmda_interactionClozapine Ă— Phencyclidine         -0.601  0.458   -1.313  
## atp_nmda_interactionHaloperidol Ă— Phencyclidine       -1.152  0.499   -2.311  
## atp_nmda_interactionOlanzapine Ă— Phencyclidine        -0.509  0.256   -1.985  
## atp_nmda_interactionQuetiapine Ă— Phencyclidine        -0.891  0.725   -1.229  
## atp_nmda_interactionRisperidone Ă— Phencyclidine       -0.679  0.410   -1.656  
## atp_nmda_interactionSulpiride Ă— Phencyclidine         -0.592  2.924   -0.202  
##                                                       dfÂą   pvalÂą    ci.lbÂą 
## atp_nmda_interactionClozapine Ă— Ketamine            1.01   0.484    -8.701  
## atp_nmda_interactionHaloperidol Ă— Ketamine          1.01   0.756    -4.538  
## atp_nmda_interactionRisperidone Ă— Ketamine             1   0.979    -5.116  
## atp_nmda_interactionAripiprazole Ă— MK-801              1   0.594    -6.366  
## atp_nmda_interactionClozapine Ă— MK-801              4.96   0.970    -0.950  
## atp_nmda_interactionHaloperidol Ă— MK-801            2.44   0.177    -1.720  
## atp_nmda_interactionRisperidone Ă— MK-801            1.08   0.503    -8.355  
## atp_nmda_interactionAripiprazole Ă— Phencyclidine      NA      NA        NA  
## atp_nmda_interactionCariprazine Ă— Phencyclidine     2.58   0.029    -2.564  
## atp_nmda_interactionChlorpromazine Ă— Phencyclidine  1.78   0.897    -1.402  
## atp_nmda_interactionClozapine Ă— Phencyclidine       2.12   0.314    -2.469  
## atp_nmda_interactionHaloperidol Ă— Phencyclidine     2.07   0.143    -3.233  
## atp_nmda_interactionOlanzapine Ă— Phencyclidine      2.29   0.169    -1.487  
## atp_nmda_interactionQuetiapine Ă— Phencyclidine      1.88   0.351    -4.210  
## atp_nmda_interactionRisperidone Ă— Phencyclidine     3.16   0.192    -1.948  
## atp_nmda_interactionSulpiride Ă— Phencyclidine          1   0.873   -37.751  
##                                                      ci.ubÂą    
## atp_nmda_interactionClozapine Ă— Ketamine             7.353     
## atp_nmda_interactionHaloperidol Ă— Ketamine           4.840     
## atp_nmda_interactionRisperidone Ă— Ketamine           5.142     
## atp_nmda_interactionAripiprazole Ă— MK-801            5.665     
## atp_nmda_interactionClozapine Ă— MK-801               0.980     
## atp_nmda_interactionHaloperidol Ă— MK-801             0.549     
## atp_nmda_interactionRisperidone Ă— MK-801             6.984     
## atp_nmda_interactionAripiprazole Ă— Phencyclidine        NA     
## atp_nmda_interactionCariprazine Ă— Phencyclidine     -0.304   * 
## atp_nmda_interactionChlorpromazine Ă— Phencyclidine   1.491     
## atp_nmda_interactionClozapine Ă— Phencyclidine        1.268     
## atp_nmda_interactionHaloperidol Ă— Phencyclidine      0.929     
## atp_nmda_interactionOlanzapine Ă— Phencyclidine       0.469     
## atp_nmda_interactionQuetiapine Ă— Phencyclidine       2.428     
## atp_nmda_interactionRisperidone Ă— Phencyclidine      0.590     
## atp_nmda_interactionSulpiride Ă— Phencyclidine       36.567     
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

Meta-regression

Cumulative exposure

## 
## Multivariate Meta-Analysis Model (k = 107; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.062  0.249     18     no         study_id 
## sigma^2.2  0.122  0.349     44     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 105) = 581.137, p-val < .001
## 
## Number of estimates:   107
## Number of clusters:    18
## Estimates per cluster: 0-20 (mean: 5.63, median: 4)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 1.15) = 25.431, p-val = 0.101
## 
## Model Results:
## 
##                          estimate     seÂą    tvalÂą    dfÂą   pvalÂą   ci.lbÂą 
## intrcpt                    -0.438  0.111   -3.947   12.8   0.002   -0.678  
## atp_cumulative_exposure    -0.010  0.002   -5.043   1.15   0.101   -0.029  
##                           ci.ubÂą     
## intrcpt                  -0.198   ** 
## atp_cumulative_exposure   0.009      
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

Meta-regression of cumulative exposure versus effect size. The regression coefficient indicates whether increasing cumulative exposure is associated with changes in effect size, suggesting a potential dose–response relationship.

Log-transformed cumulative exposure

## 
## Multivariate Meta-Analysis Model (k = 107; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.000  0.000     18     no         study_id 
## sigma^2.2  1.116  1.056     44     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 105) = 507.602, p-val < .001
## 
## Number of estimates:   107
## Number of clusters:    18
## Estimates per cluster: 0-20 (mean: 5.63, median: 4)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 4.55) = 124.051, p-val < .001
## 
## Model Results:
## 
##                              estimate     seÂą     tvalÂą    dfÂą   pvalÂą   ci.lbÂą 
## intrcpt                        -0.837  0.150    -5.589   9.94   <.001   -1.172  
## log_atp_cumulative_exposure    -1.041  0.093   -11.138   4.55   <.001   -1.289  
##                               ci.ubÂą      
## intrcpt                      -0.503   *** 
## log_atp_cumulative_exposure  -0.794   *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

Meta-regression of log-transformed cumulative exposure. The log-transformed model evaluates potential non-linear exposure–effect relationships and the robustness of the association.

Sensitivity analyses

Rho sensitivity

##   rho    estimate               ci
## 1 0.0 -0.76923519 [-0.922, -0.616]
## 2 0.3 -0.63134529 [-0.776, -0.487]
## 3 0.5 -0.49318260 [-0.682, -0.305]
## 4 0.8 -0.09590805  [-0.468, 0.276]

Sensitivity of the overall effect to within-study correlation (rho). This analysis evaluates the robustness of the pooled effect size to assumptions about the correlation between multiple effect sizes within the same experiment. Each row reports the overall effect estimate (Hedges’ g) and 95% confidence interval obtained under a different assumed value of rho. Stability of estimates across rho values indicates robustness to within-study dependency assumptions.

Leave-one-study-out

##      left_out_study   estimate      ci_lb      ci_ub
## 1       becker_2004 -0.4960334 -0.7139502 -0.2781166
## 2      corbett_1995 -0.4466817 -0.6054748 -0.2878886
## 3     gacsalyi_2013 -0.4881798 -0.6798151 -0.2965444
## 4    gururajan_2011 -0.4708840 -0.6676838 -0.2740842
## 5    gururajan_2012 -0.4830427 -0.6750026 -0.2910829
## 6       hereta_2019 -0.5026705 -0.7059116 -0.2994294
## 7     kaminska_2015 -0.5180835 -0.7072542 -0.3289127
## 8      maehara_2011 -0.5068092 -0.7001800 -0.3134384
## 9     morimoto_2002 -0.5326388 -0.6761006 -0.3891771
## 10       neill_2016 -0.4949793 -0.6918600 -0.2980986
## 11     pouzet_2002b -0.4597217 -0.6375125 -0.2819308
## 12       rung_2005b -0.5021678 -0.7036788 -0.3006569
## 13   sams-dodd_1996 -0.5164514 -0.7158479 -0.3170550
## 14   sams-dodd_1997 -0.4924735 -0.7112486 -0.2736983
## 15   sams-dodd_1998 -0.4962294 -0.7116213 -0.2808375
## 16  sams-dodd_1998d -0.4913187 -0.6899453 -0.2926920
## 17       satow_2009 -0.5124544 -0.7096829 -0.3152260
## 18     tarland_2017 -0.4648505 -0.6469680 -0.2827329
## 19 vijeepallam_2016 -0.5091156 -0.7039911 -0.3142400

Leave-one-study-out analysis. Each row reports the pooled effect size (Hedges’ g) and 95% confidence interval obtained after excluding one study at a time from the meta-analysis. This analysis evaluates the influence of individual studies on the overall estimate; substantial changes after removal of a study would indicate disproportionate influence.

Excluding high risk of bias

## 
## Multivariate Meta-Analysis Model (k = 83; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.050  0.224     10     no         study_id 
## sigma^2.2  0.105  0.324     25     no  study_id/exp_id 
## 
## Test for Heterogeneity:
## Q(df = 82) = 551.351, p-val < .001
## 
## Number of estimates:   83
## Number of clusters:    10
## Estimates per cluster: 0-20 (mean: 4.37, median: 2)
## 
## Model Results:
## 
## estimate     seÂą    tvalÂą    dfÂą   pvalÂą   ci.lbÂą   ci.ubÂą    
##   -0.409  0.130   -3.150   6.94   0.016   -0.717   -0.102   * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t-test and confidence interval, df: Satterthwaite approx)

Overall effect excluding high risk-of-bias studies. This sensitivity analysis re-estimates the overall meta-analytic effect after excluding studies classified as having high risk of bias. The purpose of this analysis is to assess whether the pooled effect estimate is robust to the exclusion of potentially biased evidence.

Annex: Individual effect sizes included in the meta-analysis

Calculated effect sizes

## 
##                study effect_id species nmda_antagonist       atp_drug hedges_g 
## 1     Gururajan 2011         7     Rat          MK-801      Clozapine   -0.958 
## 2     Gururajan 2011         8     Rat          MK-801      Clozapine   -1.387 
## 3     Gururajan 2011         9     Rat          MK-801      Clozapine   -1.935 
## 4     Gururajan 2011        13     Rat          MK-801      Clozapine    0.400 
## 5     Gururajan 2011        14     Rat          MK-801      Clozapine   -0.844 
## 6     Gururajan 2011        15     Rat          MK-801      Clozapine   -0.869 
## 7     Sams-Dodd 1997        33     Rat   Phencyclidine    Risperidone   -0.272 
## 8     Sams-Dodd 1997        39     Rat   Phencyclidine    Risperidone    0.765 
## 9     Sams-Dodd 1997        34     Rat   Phencyclidine    Risperidone   -1.590 
## 10    Sams-Dodd 1997        40     Rat   Phencyclidine    Risperidone   -0.765 
## 11    Sams-Dodd 1997        57     Rat   Phencyclidine     Quetiapine   -0.274 
## 12    Sams-Dodd 1997        65     Rat   Phencyclidine     Quetiapine   -0.406 
## 13    Sams-Dodd 1997        46     Rat   Phencyclidine     Olanzapine   -0.578 
## 14    Sams-Dodd 1997        51     Rat   Phencyclidine     Olanzapine   -0.095 
## 15    Sams-Dodd 1997        35     Rat   Phencyclidine    Risperidone   -3.189 
## 16    Sams-Dodd 1997        41     Rat   Phencyclidine    Risperidone   -1.907 
## 17    Sams-Dodd 1997        58     Rat   Phencyclidine     Quetiapine   -0.886 
## 18    Sams-Dodd 1997        66     Rat   Phencyclidine     Quetiapine   -0.931 
## 19    Sams-Dodd 1997        47     Rat   Phencyclidine     Olanzapine   -0.872 
## 20    Sams-Dodd 1997        52     Rat   Phencyclidine     Olanzapine    0.069 
## 21    Sams-Dodd 1997        53     Rat   Phencyclidine     Olanzapine   -1.621 
## 22    Sams-Dodd 1997        59     Rat   Phencyclidine     Quetiapine   -0.809 
## 23    Sams-Dodd 1997        67     Rat   Phencyclidine     Quetiapine   -1.457 
## 24    Sams-Dodd 1997        48     Rat   Phencyclidine     Olanzapine   -4.463 
## 25    Sams-Dodd 1997        60     Rat   Phencyclidine     Quetiapine   -1.939 
## 26    Sams-Dodd 1997        68     Rat   Phencyclidine     Quetiapine   -1.546 
## 27    Sams-Dodd 1998        95     Rat   Phencyclidine      Clozapine    0.153 
## 28    Sams-Dodd 1998        73     Rat   Phencyclidine    Haloperidol   -0.136 
## 29    Sams-Dodd 1998        81     Rat   Phencyclidine    Haloperidol   -0.277 
## 30    Sams-Dodd 1998        89     Rat   Phencyclidine      Clozapine   -0.256 
## 31    Sams-Dodd 1998        96     Rat   Phencyclidine      Clozapine   -0.316 
## 32    Sams-Dodd 1998        74     Rat   Phencyclidine    Haloperidol   -0.835 
## 33    Sams-Dodd 1998        82     Rat   Phencyclidine    Haloperidol   -1.405 
## 34    Sams-Dodd 1998        90     Rat   Phencyclidine      Clozapine   -0.969 
## 35    Sams-Dodd 1998        97     Rat   Phencyclidine      Clozapine   -0.058 
## 36    Sams-Dodd 1998        75     Rat   Phencyclidine    Haloperidol   -1.780 
## 37    Sams-Dodd 1998        83     Rat   Phencyclidine    Haloperidol   -0.710 
## 38    Sams-Dodd 1998        76     Rat   Phencyclidine    Haloperidol   -3.538 
## 39    Sams-Dodd 1998        84     Rat   Phencyclidine    Haloperidol   -0.788 
## 40    Sams-Dodd 1998        98     Rat   Phencyclidine      Clozapine   -0.303 
## 41    Sams-Dodd 1998        91     Rat   Phencyclidine      Clozapine   -1.386 
## 42     Pouzet 2002 b       136     Rat   Phencyclidine    Risperidone   -2.409 
## 43     Pouzet 2002 b       137     Rat   Phencyclidine    Risperidone   -5.003 
## 44     Kaminska 2015       179     Rat          MK-801    Risperidone   -0.204 
## 45     Kaminska 2015       185     Rat          MK-801    Risperidone    0.101 
## 46     Kaminska 2015       180     Rat          MK-801    Risperidone    0.275 
## 47      Maehara 2011       188     Rat          MK-801      Clozapine   -0.050 
## 48      Maehara 2011       189     Rat          MK-801      Clozapine   -0.065 
## 49     Gacsalyi 2013       212     Rat   Phencyclidine     Olanzapine   -0.877 
## 50        Neill 2016       225     Rat   Phencyclidine    Cariprazine   -0.081 
## 51        Neill 2016       226     Rat   Phencyclidine    Cariprazine   -1.368 
## 52        Neill 2016       228     Rat   Phencyclidine    Risperidone   -0.164 
## 53        Neill 2016       227     Rat   Phencyclidine    Cariprazine   -2.230 
## 54    Sams-Dodd 1996       233     Rat   Phencyclidine    Haloperidol    1.234 
## 55    Sams-Dodd 1996       234     Rat   Phencyclidine    Haloperidol   -2.592 
## 56    Sams-Dodd 1996       243     Rat   Phencyclidine      Clozapine    0.293 
## 57    Sams-Dodd 1996       244     Rat   Phencyclidine      Clozapine   -1.177 
## 58    Sams-Dodd 1996       239     Rat   Phencyclidine    Haloperidol    0.089 
## 59    Sams-Dodd 1996       240     Rat   Phencyclidine    Haloperidol   -1.150 
## 60    Sams-Dodd 1996       241     Rat   Phencyclidine    Haloperidol   -4.930 
## 61    Sams-Dodd 1996       251     Rat   Phencyclidine      Clozapine   -0.079 
## 62    Sams-Dodd 1996       242     Rat   Phencyclidine    Haloperidol   -2.926 
## 63    Sams-Dodd 1996       252     Rat   Phencyclidine      Clozapine   -1.260 
## 64    Sams-Dodd 1996       253     Rat   Phencyclidine      Clozapine   -1.533 
## 65    Sams-Dodd 1996       254     Rat   Phencyclidine      Clozapine   -2.002 
## 66  Sams-Dodd 1998 d       259     Rat   Phencyclidine      Sulpiride   -0.155 
## 67  Sams-Dodd 1998 d       260     Rat   Phencyclidine      Sulpiride   -0.550 
## 68  Sams-Dodd 1998 d       261     Rat   Phencyclidine      Sulpiride   -0.927 
## 69  Sams-Dodd 1998 d       262     Rat   Phencyclidine      Sulpiride   -2.223 
## 70  Vijeepallam 2016       268   Mouse        Ketamine      Clozapine   -0.111 
## 71       Becker 2004       295     Rat        Ketamine    Risperidone   -0.635 
## 72       Becker 2004       292     Rat        Ketamine      Clozapine   -8.925 
## 73       Becker 2004       283     Rat        Ketamine    Haloperidol    0.155 
## 74       Becker 2004       289     Rat        Ketamine    Risperidone   -0.205 
## 75       Becker 2004       286     Rat        Ketamine      Clozapine   -0.668 
## 76       Becker 2004       274     Rat        Ketamine    Haloperidol   -0.461 
## 77       Becker 2004       280     Rat        Ketamine    Risperidone   -0.152 
## 78       Becker 2004       277     Rat        Ketamine      Clozapine   -0.835 
## 79        Satow 2009       316     Rat          MK-801    Haloperidol    0.295 
## 80        Satow 2009       317     Rat          MK-801    Haloperidol   -2.190 
## 81        Satow 2009       318     Rat          MK-801    Haloperidol   -1.077 
## 82        Satow 2009       319     Rat          MK-801    Haloperidol   -2.979 
## 83        Satow 2009       322     Rat          MK-801      Clozapine    0.365 
## 84        Satow 2009       323     Rat          MK-801      Clozapine    0.361 
## 85      Tarland 2017       334     Rat   Phencyclidine   Aripiprazole   -2.021 
## 86      Corbett 1995       375     Rat   Phencyclidine    Risperidone   -0.251 
## 87      Corbett 1995       367     Rat   Phencyclidine    Haloperidol   -2.995 
## 88      Corbett 1995       376     Rat   Phencyclidine    Risperidone   -1.752 
## 89      Corbett 1995       368     Rat   Phencyclidine    Haloperidol   -4.675 
## 90      Corbett 1995       383     Rat   Phencyclidine     Olanzapine   -0.478 
## 91      Corbett 1995       384     Rat   Phencyclidine     Olanzapine   -1.805 
## 92      Corbett 1995       371     Rat   Phencyclidine Chlorpromazine    0.161 
## 93      Corbett 1995       372     Rat   Phencyclidine Chlorpromazine   -1.283 
## 94      Corbett 1995       379     Rat   Phencyclidine      Clozapine   -1.165 
## 95      Corbett 1995       380     Rat   Phencyclidine      Clozapine   -1.063 
## 96    Gururajan 2012       392     Rat          MK-801      Clozapine   -1.427 
## 97    Gururajan 2012       393     Rat          MK-801      Clozapine   -0.696 
## 98       Hereta 2019       404     Rat          MK-801   Aripiprazole   -0.804 
## 99       Hereta 2019       405     Rat          MK-801   Aripiprazole   -0.316 
## 100      Hereta 2019       410     Rat          MK-801   Aripiprazole    0.543 
## 101      Hereta 2019       413     Rat          MK-801   Aripiprazole   -0.794 
## 102      Hereta 2019       406     Rat          MK-801   Aripiprazole   -1.058 
## 103      Hereta 2019       407     Rat          MK-801   Aripiprazole   -0.719 
## 104    Morimoto 2002       444     Rat          MK-801    Risperidone   -1.235 
## 105    Morimoto 2002       445     Rat          MK-801    Risperidone   -0.147 
## 106    Morimoto 2002       446     Rat          MK-801    Risperidone   -1.429 
## 107    Morimoto 2002       447     Rat          MK-801    Risperidone   -3.258 
## 108    Morimoto 2002       422     Rat          MK-801      Clozapine   -0.167 
## 109    Morimoto 2002       423     Rat          MK-801      Clozapine    0.893 
## 110    Morimoto 2002       424     Rat          MK-801      Clozapine    0.531 
## 111    Morimoto 2002       425     Rat          MK-801      Clozapine   -1.141 
## 112    Morimoto 2002       426     Rat          MK-801      Clozapine   -9.484 
## 113    Morimoto 2002       431     Rat          MK-801    Haloperidol   -0.189 
## 114    Morimoto 2002       432     Rat          MK-801    Haloperidol   -0.386 
## 115    Morimoto 2002       433     Rat          MK-801    Haloperidol   -1.756 
## 116    Morimoto 2002       434     Rat          MK-801    Haloperidol   -6.697 
## 117      Rung 2005 b       463     Rat          MK-801    Haloperidol   -0.233 
## 118      Rung 2005 b       464     Rat          MK-801    Haloperidol   -2.953 
## 119      Rung 2005 b       465     Rat          MK-801    Haloperidol   -3.768 
## 120      Rung 2005 b       469     Rat          MK-801      Clozapine    0.115 
## 121      Rung 2005 b       470     Rat          MK-801      Clozapine    0.281 
## 122      Rung 2005 b       471     Rat          MK-801      Clozapine   -0.102 
##       ci_lb  ci_ub 
## 1    -1.883 -0.032 
## 2    -2.363 -0.411 
## 3    -2.997 -0.873 
## 4    -0.485  1.285 
## 5    -1.759  0.071 
## 6    -1.786  0.048 
## 7    -1.076  0.532 
## 8    -0.064  1.593 
## 9    -2.508 -0.672 
## 10   -1.594  0.064 
## 11   -1.078  0.530 
## 12   -1.214  0.402 
## 13   -1.394  0.239 
## 14   -0.896  0.705 
## 15   -4.395 -1.983 
## 16   -2.872 -0.942 
## 17   -1.724 -0.047 
## 18   -1.774 -0.089 
## 19   -1.709 -0.035 
## 20   -0.732  0.869 
## 21   -2.543 -0.698 
## 22   -1.641  0.023 
## 23   -2.357 -0.557 
## 24   -5.957 -2.968 
## 25   -2.909 -0.969 
## 26   -2.648 -0.443 
## 27   -0.648  0.954 
## 28   -0.937  0.665 
## 29   -1.081  0.527 
## 30   -1.059  0.547 
## 31   -1.122  0.489 
## 32   -1.670 -0.001 
## 33   -2.299 -0.512 
## 34   -1.815 -0.123 
## 35   -0.858  0.743 
## 36   -2.726 -0.835 
## 37   -1.535  0.115 
## 38   -4.819 -2.256 
## 39   -1.618  0.043 
## 40   -1.108  0.502 
## 41   -2.277 -0.495 
## 42   -3.895 -0.923 
## 43   -7.302 -2.703 
## 44   -1.339  0.930 
## 45   -1.031  1.234 
## 46   -0.862  1.412 
## 47   -1.083  0.984 
## 48   -1.099  0.968 
## 49   -2.328  0.574 
## 50   -1.062  0.899 
## 51   -2.457 -0.280 
## 52   -1.146  0.818 
## 53   -3.478 -0.982 
## 54    0.361  2.107 
## 55   -3.677 -1.507 
## 56   -0.511  1.097 
## 57   -2.043 -0.310 
## 58   -0.711  0.890 
## 59   -2.013 -0.286 
## 60   -6.538 -3.322 
## 61   -0.879  0.722 
## 62   -4.078 -1.775 
## 63   -2.136 -0.384 
## 64   -2.443 -0.623 
## 65   -2.982 -1.022 
## 66   -0.957  0.646 
## 67   -1.366  0.265 
## 68   -1.769 -0.085 
## 69   -3.241 -1.205 
## 70   -0.804  0.583 
## 71   -1.538  0.268 
## 72  -12.396 -5.454 
## 73   -0.861  1.171 
## 74   -1.064  0.653 
## 75   -1.573  0.237 
## 76   -1.328  0.407 
## 77   -0.989  0.685 
## 78   -1.864  0.195 
## 79   -0.656  1.246 
## 80   -3.345 -1.034 
## 81   -1.958 -0.196 
## 82   -4.555 -1.403 
## 83   -0.776  1.506 
## 84   -0.779  1.502 
## 85   -3.308 -0.733 
## 86   -1.388  0.885 
## 87   -4.643 -1.347 
## 88   -3.083 -0.421 
## 89   -6.862 -2.489 
## 90   -1.625  0.670 
## 91   -3.148 -0.463 
## 92   -0.973  1.294 
## 93   -2.526 -0.041 
## 94   -2.389  0.059 
## 95   -2.272  0.146 
## 96   -2.816 -0.039 
## 97   -1.972  0.581 
## 98   -1.981  0.372 
## 99   -1.454  0.823 
## 100  -0.609  1.695 
## 101  -1.969  0.381 
## 102  -2.267  0.150 
## 103  -1.886  0.449 
## 104  -2.588  0.117 
## 105  -1.389  1.094 
## 106  -2.818 -0.040 
## 107  -5.149 -1.367 
## 108  -1.409  1.075 
## 109  -0.407  2.193 
## 110  -0.731  1.792 
## 111  -2.478  0.196 
## 112 -13.822 -5.147 
## 113  -1.431  1.053 
## 114  -1.637  0.866 
## 115  -3.215 -0.297 
## 116  -9.883 -3.511 
## 117  -1.161  0.694 
## 118  -4.289 -1.617 
## 119  -5.307 -2.229 
## 120  -1.017  1.248 
## 121  -0.856  1.419 
## 122  -1.234  1.030

Individual effect sizes included in the meta-analysis. This table lists all calculated Hedges’ g values and corresponding confidence intervals used in the analyses.

Session info

## R version 4.3.1 (2023-06-16 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 11 x64 (build 26100)
## 
## Matrix products: default
## 
## 
## locale:
## [1] LC_COLLATE=Portuguese_Brazil.utf8  LC_CTYPE=Portuguese_Brazil.utf8   
## [3] LC_MONETARY=Portuguese_Brazil.utf8 LC_NUMERIC=C                      
## [5] LC_TIME=Portuguese_Brazil.utf8    
## 
## time zone: America/Sao_Paulo
## tzcode source: internal
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] RColorBrewer_1.1-3  scales_1.4.0        stringr_1.5.1      
##  [4] forcats_1.0.1       ggalluvial_0.12.5   tidyr_1.3.1        
##  [7] ggplot2_4.0.0       orchaRd_2.1.3       clubSandwich_0.6.1 
## [10] metafor_4.8-0       numDeriv_2016.8-1.1 metadat_1.2-0      
## [13] Matrix_1.6-5        dplyr_1.1.4         readxl_1.4.5       
## 
## loaded via a namespace (and not attached):
##  [1] gtable_0.3.6       beeswarm_0.4.0     xfun_0.52          bslib_0.9.0       
##  [5] lattice_0.22-6     mathjaxr_1.6-0     vctrs_0.6.5        tools_4.3.1       
##  [9] generics_0.1.4     sandwich_3.1-1     tibble_3.2.1       pkgconfig_2.0.3   
## [13] S7_0.2.0           lifecycle_1.0.4    compiler_4.3.1     farver_2.1.2      
## [17] textshaping_1.0.0  prettydoc_0.4.1    codetools_0.2-20   vipor_0.4.7       
## [21] htmltools_0.5.8.1  sass_0.4.9         yaml_2.3.10        pillar_1.11.1     
## [25] jquerylib_0.1.4    MASS_7.3-60.0.1    cachem_1.1.0       multcomp_1.4-28   
## [29] nlme_3.1-164       tidyselect_1.2.1   digest_0.6.35      mvtnorm_1.3-3     
## [33] stringi_1.8.7      purrr_1.0.2        labeling_0.4.3     splines_4.3.1     
## [37] latex2exp_0.9.6    fastmap_1.2.0      grid_4.3.1         cli_3.6.2         
## [41] magrittr_2.0.3     survival_3.5-8     TH.data_1.1-4      withr_3.0.2       
## [45] ggbeeswarm_0.7.2   estimability_1.5.1 rmarkdown_2.30     emmeans_1.11.2-8  
## [49] cellranger_1.1.0   ragg_1.3.3         zoo_1.8-13         evaluate_1.0.5    
## [53] knitr_1.50         rlang_1.1.5        xtable_1.8-4       glue_1.8.0        
## [57] rstudioapi_0.17.1  jsonlite_2.0.0     R6_2.6.1           systemfonts_1.2.2